Please wait a minute...
Chin. Phys. B, 2015, Vol. 24(11): 110201    DOI: 10.1088/1674-1056/24/11/110201
GENERAL   Next  

Direction-of-arrival estimation for co-located multiple-input multiple-output radar using structural sparsity Bayesian learning

Wen Fang-Qing (文方青)a b, Zhang Gong (张弓)a b, Ben De (贲德)a b c
a College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;
b Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education, Nanjing 210016, China;
c Nanjing Research Institute of Electronics Technology, Nanjing 210039, China
Abstract  This paper addresses the direction of arrival (DOA) estimation problem for the co-located multiple-input multiple-output (MIMO) radar with random arrays. The spatially distributed sparsity of the targets in the background makes compressive sensing (CS) desirable for DOA estimation. A spatial CS framework is presented, which links the DOA estimation problem to support recovery from a known over-complete dictionary. A modified statistical model is developed to accurately represent the intra-block correlation of the received signal. A structural sparsity Bayesian learning algorithm is proposed for the sparse recovery problem. The proposed algorithm, which exploits intra-signal correlation, is capable being applied to limited data support and low signal-to-noise ratio (SNR) scene. Furthermore, the proposed algorithm has less computation load compared to the classical Bayesian algorithm. Simulation results show that the proposed algorithm has a more accurate DOA estimation than the traditional multiple signal classification (MUSIC) algorithm and other CS recovery algorithms.
Keywords:  multiple-input multiple-output radar      random arrays      direction of arrival estimation      sparse Bayesian learning  
Received:  27 March 2015      Revised:  18 June 2015      Accepted manuscript online: 
PACS:  02.30.Zz (Inverse problems)  
  02.50.-r (Probability theory, stochastic processes, and statistics)  
  87.16.dt (Structure, static correlations, domains, and rafts)  
Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 61071163, 61271327, and 61471191), the Funding for Outstanding Doctoral Dissertation in Nanjing University of Aeronautics and Astronautics, China (Grant No. BCXJ14-08), the Funding of Innovation Program for Graduate Education of Jiangsu Province, China (Grant No. KYLX 0277), the Fundamental Research Funds for the Central Universities, China (Grant No. 3082015NP2015504), and the Priority Academic Program Development of Jiangsu Higher Education Institutions (PADA), China.
Corresponding Authors:  Zhang Gong     E-mail:  gzhang@nuaa.edu.cn

Cite this article: 

Wen Fang-Qing (文方青), Zhang Gong (张弓), Ben De (贲德) Direction-of-arrival estimation for co-located multiple-input multiple-output radar using structural sparsity Bayesian learning 2015 Chin. Phys. B 24 110201

[1] Fishler E, Haimovich A, Blum R, Chizhik D, Cimini L and Valenzuela R 2004 IEEE Radar Conference, April 26-29, 2004, Philadelphia, Pennsylvania, p. 71
[2] Xiao S, Cai J J, Wang R L, Liu M Z and Liu F;2009 Chin. Phys. B 18 5103
[3] Huang C, Zhang D J, Zhang D L and Teng T T;2014 Acta Phys. Sin. 63 188401 (in Chinese)
[4] Larsson E G, Edfors O, Tufvesson F and Marzetta T L;2014 IEEE Commun. Mag. 52 186
[5] Duan H P, Ng B P, See C M S and Fang J;2008 IEEE Trans. Signal Process. 56 2406
[6] Wen F Q and Zhang G 2013 Math. Prob. Eng. 2013 427980
[7] Rossi M, Haimovich A M and Eldar Y C 2014 IEEE Trans. Signal Process. 62 419
[8] Schmidt R O;1986 IEEE Trans. Antennas Propag. 34 276
[9] Roy R and Kailath;1989 IEEE Trans. Acous. Speech Signal Process. 37 984
[10] Cotter S F, Rao B D, Engan K and Kenneth K D;2005 IEEE Trans. Signal Process. 53 2477
[11] Cand’es E J, Romberg J and Tao T;2006 IEEE Trans. Inform. Theory 52 489
[12] Sun Y L and Tao J X;2014 Chin. Phys. B 23 078703
[13] Tropp J A and Gilbert A C;2007 IEEE Trans. Inform. Theory 53 4655
[14] Ning F L, He B J and Wei J;2013 Acta Phys. Sin 62 174214 (in Chinese)
[15] Wipf D P and Rao B D;2007 IEEE Trans. Signal Process. 55 3704
[16] Zhang Z L and Rao B D;2011 IEEE J-STARS 5 912
[17] Eldar Y C and Mishali M;2009 IEEE Trans. Inform. Theory 55 5302
[18] Huang S X, Zhao X F and Sheng Z;2009 Chin. Phys. B 18 5084
[19] Sheng Z;2013 Chin. Phys. B 22 029302
[20] Zhang Z L and Rao B D;2013 IEEE Trans. Signal Process. 61 2009
[21] Negahban S and Wainwright M J;2011 IEEE Trans. Inform. Theory 57 3841
[22] Zhao J, Yu L and Li J R;2013 Acta Phys. Sin. 62 130201 (in Chinese)
[23] Wen F Q, Zhang G and Ben D;2015 Acta Phys. Sin. 64 070201 (in Chinese)
[24] Chen C E, Lorenzelli F, Hudson R E and Yao K;2008 IEEE Trans. Signal Process. 56 3038
[25] Liu Z M, Huang Z T and Zhou Y Y 2012 IEEE Trans. Wirel. Commun. 10 1
[26] Zhang Y, Ye Z, Xu X and Hu N 2014 Signal Process. 98 197
[27] Sun B, Chen H, Wei X and Li X 2014 Int. J. Antenn. Propag. 2014 903902
[1] Four-dimensional parameter estimation of plane waves using swarming intelligence
Fawad Zaman, Ijaz Mansoor Qureshi, Fahad Munir, Zafar Ullah Khan. Chin. Phys. B, 2014, 23(7): 078402.
No Suggested Reading articles found!